def test_passes(self, data):
n_passes = 2
model = VW(loss_function='logistic', passes=n_passes)
assert model.passes_ == n_passes
model.fit(data.x, data.y)
weights = model.get_coefs()
model = VW(loss_function='logistic')
# first pass weights should not be the same
model.fit(data.x, data.y)
assert not np.allclose(weights.data, model.get_coefs().data)
# second pass weights should match
model.fit(data.x, data.y)
assert np.allclose(weights.data, model.get_coefs().data)
def test_get_coefs(self, data):
model = VW()
model.fit(data.x, data.y)
weights = model.get_coefs()
print weights.data
assert np.allclose(weights.indices,
[0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 116060])
def test_get_coefs(self, data):
model = VW()
model.fit(data.x, data.y)
weights = model.get_coefs()
print weights.data
assert np.allclose(weights.indices, [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 116060])
assert np.allclose(weights.data, [0.11553502, -0.0166647, -0.00349924, 0.06911729, 0.00252684,
-0.00826817, 0.01991862, -0.02473332, 0.00483846, -0.04616702, -0.00744559])
def test_get_coefs(self, data):
model = VW()
model.fit(data.x, data.y)
weights = model.get_coefs()
print weights.data
assert np.allclose(weights.indices, [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 116060])
